Force and Vision Resolvability for Assimilating Disparate Sensory Feedback.

Abstract

Force and vision sensors provide complementary information, yet they are fundamentally different sensing modalities. This implies that traditional sensor integration techniques that require common data representations are not appropriate for combining the feedback from these two disparate sensor. In this paper, we introduce the concept of vision and force sensor resolvability as a means of comparing the ability of the two sensing modes to provide useful information during robotic manipulation tasks. By monitoring the resolvability of the two sensing modes with respect to the task, the information provided by the disparate sensors can be seamlessly assimilated during task execution. A nonlinear force/vision serving algorithm that uses force and vision resolvability to switch between sensing modes is proposed. The advantages of the assimilation technique is demonstrated during contact transitions between a stiff manipulator and rigid environment, a system configuration that easily becomes unstable when force control alone is used. Experimental results show that robust contact transitions are made by the proposed nonlinear controller while simultaneously satisfying the conflicting task requirements of fast approach velocities, maintaining stability, minimizing impact forces, and suppressing bounce between contact surfaces.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1995
Accession Number
ADA293581

Entities

People

  • Bradley J. Nelson
  • Pradeep K. Khosla

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Accuracy
  • Automata Theory
  • Automation
  • Computer Vision
  • Control Systems
  • Equations
  • Measurement
  • New York
  • Object Recognition
  • Operating Systems
  • Orientation (Direction)
  • Pattern Recognition
  • Robotics
  • Robots
  • Strain Gages
  • Three Dimensional
  • Visual Servoing

Readers

  • Radar Systems Engineering.
  • Robotics and Automation.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • Autonomy
  • Autonomy - Autonomous System Control